Sixteen years ago, on a cold February day at Yale University, a poster caught Gil Kalai’s eye. It advertised a series of lectures by Michel Devoret, a well-known expert on experimental efforts in quantum computing. The talks promised to explore the question “Quantum Computer: Miracle or Mirage?” Kalai expected a vigorous discussion of the pros and cons of quantum computing. Instead, he recalled, “the skeptical direction was a little bit neglected.” He set out to explore that skeptical view himself. Today, Kalai, a mathematician at Hebrew University in Jerusalem, is one of the most prominent of a loose group of mathematicians, physicists and computer scientists arguing that quantum computing, for all its theoretical promise, is something of a mirage. Some argue that there exist good theoretical reasons why the innards of a quantum computer — the “qubits” — will never be able to consistently perform the complex choreography asked of them. Others say that the machines will never work in practice, or that if they are built, their advantages won’t be great enough to make up for the expense.

Due to the interdisciplinary nature of complex systems as a field, students studying complex systems at University level have diverse disciplinary backgrounds. This brings challenges (e.g. wide range of computer programming skills) but also opportunities (e.g. facilitating interdisciplinary interactions and projects) for the classroom. However, there is little published regarding how these challenges and opportunities are handled in teaching and learning Complex Systems as an explicit subject in higher education, and how this differs in comparison to other subject areas. We seek to explore these particular challenges and opportunities via an interview-based study of pioneering teachers and learners (conducted amongst the authors) regarding their experiences. We compare and contrast those experiences, and analyse them with respect to the educational literature. Our discussions explored: approaches to curriculum design, how theories/models/frameworks of teaching and learning informed decisions and experience, how diversity in student backgrounds was addressed, and assessment task design. We found a striking level of commonality in the issues expressed as well as the strategies to handle them, for example a significant focus on problem-based learning, and the use of major student-led creative projects for both achieving and assessing learning outcomes.

Why, all of a sudden, are so many successful business leaders urging their companies and colleagues to make more mistakes and embrace more failures? In May, right after he became CEO of Coca-Cola Co., James Quincey called upon rank-and-file managers to get beyond the fear of failure that had dogged the company since the “New Coke” fiasco of so many years ago. “If we’re not making mistakes,” he insisted, “we’re not trying hard enough.” In June, even as his company was enjoying unparalleled success with its subscribers, Netflix CEO Reed Hastings worried that his fabulously valuable streaming service had too many hit shows and was canceling too few new shows. “Our hit ratio is too high right now,” he told a technology conference. “We have to take more risk…to try more crazy things…we should have a higher cancel rate overall.”

OVERVIEW: The ultimate proof of our understanding of complex systems is reflected in our ability to control them. Although control theory offers mathematical tools for steering engineered systems towards a desired state, a framework to control complex systems is lacking. In this talk I will show that many dynamic properties of complex systems can studied be quantitatively, via a combination of tools from control theory, network science and statistical physics. In particular, I will focus on two dual concepts, i.e. controllability and observability, of general complex systems. Controllability concerns our ability to drive the system from any initial state to any final state within finite time, while observability concerns the possibility of deducing the system's internal state from observing its input-output behavior. I will show that by exploring the underlying network structure of complex systems one can determine the driver (or sensor) nodes that with time-dependent inputs (or measurements) will enable us to fully control (or observe) the whole system.Summer School in cognitive Science: Web Science and the Mind Institut des sciences cognitives, UQAM, Montréal, Canada http://www.summer14.isc.uqam.ca

Brain function is reflected in connectome community structure. The dominant view is thatcommunities are assortative and segregated from one another, supporting specializedinformation processing. However, this view precludes the possibility of non-assortativecommunities whose complex inter-community interactions could engender a richer functionalrepertoire. We use weighted stochastic blockmodels to uncover the meso-scale architectureofDrosophila, mouse, rat, macaque, and human connectomes. Wefind that most commu-nities are assortative, though others form core-periphery and disassortative structures, whichbetter recapitulate observed patterns of functional connectivity and gene co-expression inhuman and mouse connectomes compared to standard community detection techniques. Wedefine measures for quantifying the diversity of communities in which brain regions parti-cipate, showing that this measure is peaked in control and subcortical systems in humans,and that inter-individual differences are correlated with cognitive performance. Our reportpaints a more diverse portrait of connectome communities and demonstrates their cognitiverelevance

Abstract This article explores the dynamics between government and human service nonprofits for service delivery in the United States. The authors initiate the development of a dynamic resource theory to explain the process of government–nonprofit interdependence for human service delivery. The theory is conceived from the application of system dynamics to dependencies arising through the process of resource exchange. They explain how government regulations can help to improve or to lower the quality of service and how the balance of power between government and nonprofits shifts over time. Elaboration, refinement, and testing of dynamic resource theory will improve our ability to manage and benefit from the government–nonprofit partnership.

When creating a strategy for your organization there are many obstacles. It's important to know what they are and how to get around them.

Peter Drucker famously said that “culture eats strategy for breakfast.” Nowhere is that more evident than in meetings to decide corporate strategies. In those rooms, egos and competing agendas, biases and social games reign. That’s because strategy isn’t the only thing at stake. Jobs - even careers - are on the line. How biases politics and egos derail business decisions The budget process intrudes, too. You may be discussing a five-year strategy, but everyone knows that what really matters is getting a “yes” to the first-year budget. The outcome of all these dynamics is the Hockey stick projection, confidently showing future success after a dip to account for first-year spending—a bold forecast that, more often than not, fails to materialize.

The human brain is an odd, glitchy machine that is influenced in all sorts of weird ways you never thought of. The world is full of shady self-help gurus and workplace seminars telling us how we can turn our lives around just by using the right words ("Don't say the cheese is 'spoiled' -- say it's 'aged'!"), as if language is a form of magic that can alter reality. But here's the thing: The human brain is an odd, glitchy machine that is influenced in all sorts of weird ways you never thought of. This is why politicians and salespeople can trick you into going along with them, just by toying with the words they use. Science is just now catching up to them, and has found that ...

The development of advanced neuroimaging techniques and their deployment in large cohorts has enabled an assessment of functional and structural brain network architecture at an unprecedented level of detail. Across many temporal and spatial scales, network neuroscience has emerged as a central focus of intellectual efforts, seeking meaningful descriptions of brain networks and explanatory sets of network features that underlie circuit function in health and dysfunction in disease. However, the tools of network science commonly deployed provide insight into brain function at a fundamentally descriptive level, often failing to identify (patho-)physiological mechanisms that link system-level phenomena to the multiple hierarchies of brain function. Here we describe recently developed techniques stemming from advances in complex systems and network science that have the potential to overcome this limitation, thereby contributing mechanistic insights into neuroanatomy, functional dynamics, and pathology. Finally, we build on the Research Domain Criteria framework, highlighting the notion that mental illnesses can be conceptualized as dysfunctions of neural circuitry present across conventional diagnostic boundaries, to sketch how network-based methods can be combined with pharmacological, intermediate phenotype, genetic, and magnetic stimulation studies to probe mechanisms of psychopathology.

ABSTRACT : The philosophy of complexity, in recent decades, has set up and consolidatedan epistemological approach that describes the nature often in terms of case and possibil-ity . This paradigm also calls, especially in the works of Edgar Morin, to overcome thebar riers between dierent disciplines and suggests a fruitful fusion between the studyof physics, biology and anthropology and social sciences. On the basis of this approach,this paper investigates the relationship between musical improvisation and complexity,trying to highlight that the aesthetics of the unexpected, which is realized in the perfor-mances of improvisational groups, represents a phenomenon in which there are obviousisomorphisms with the systemic organization. Isomorphisms which are characterizedby the dialectical relationship chaos-order , the genesic mechanisms of back-action, in-tegration of contingency and the central role of the concept of emergency. For thisreason, musical improvisation may be considered as a dynamic adaptive system and like anactivity situated between aesthetics and ontology.

Einstein inspired a paradigm shift in physics not as a scientist but as an artist. Our entire construct of the world depends on language. What we see isn’t what the universe has defined, but what our brains have learned to label. English distinguishes a scientist as someone who systematically learns about a part of the natural world and uses that knowledge to describe and predict it. An artist, on the other hand, is defined as someone who creatively produces. These labels are important. They’re not perfect, but they allow us to differentiate between the different aspects of our reality. The harm occurs when we use them incorrectly. When it comes to categories like science and art, we have a tendency to presume mutual exclusivity. Einstein may have been a practicing scientist with a focus on theoretical physics, but that doesn’t mean that he wasn’t also an artist. In fact, we can easily argue that more of his success was attributed to his creativity than it was to his underlying knowledge of the field. There are many smart and knowledgeable scientists. Rarely, however, are they capable of producing work that shifts our entire understanding of the world. That requires an entirely new way of looking at things. You don’t have to play the violin or write a poem to be an artist. It’s simply about producing, and the quality of what you produce is largely dependent on creativity. Believe it or not, there isn’t as much to it as you might think. 1. Don’t Wait for Inspiration to Get Moving There are many misconceptions about how breakthroughs are made. It’s easy to fall into the trap of thinking that they’re suddenly inspired — like the often told story of the moment the fall of an apple led Newton to discover gravity. In a slight way, they do happen, and sometimes, sporadically. That said, if your sole tactic is to sit and wait for inspiration to strike, then you’re almost always setting yourself up for failure. Dr. Mark Beeman leads the Creative Brain Lab at Northwestern University. He uses brain scanners to conduct research studies to understand the creative process. In his own words: “Although the experience of insight is sudden and can seem disconnected from the immediately preceding thought, these studies show that insight is the culmination of a series of brain states and processes operating at different time scales.” Simply put, eureka moments occur because of the work leading up to them. Action stimulates inspiration more often than inspiration stimulates action. 2. Treat It Like an Unsexy Job Doing creative work isn’t sexy. It’s about setting a schedule and just doing it. In 1902, Einstein got a job at a Swiss patent office. He had searched for a teaching position in the preceding years with little luck. This forced him into an inopportune and uninspiring place relative to his interest in physics. During his time there, however, he chose to manage his day so that he had a disciplined balance between the hours he spent on the job and the hours he dedicated to scientific work. He was deliberate in his commitment to creation, and the fruits of his labor led to the Annus Mirabilis papers. Scientists call it the miracle year. It would inspire the formulation of the two fundamental theories in physics: the theory of general relativity and quantum mechanics. Had Einstein waited for the right moment, the world might not be where it is. The best way to create is to treat it as a job. Pick a time, show up, and produce. 3. Seek Relationships Between Existing Ideas At its core, creativity is just a new and useful way of combining old ideas. It isn’t imagined out of thin air, and it isn’t completely abstract. It’s a fresh way of making sense of the existing components of reality that have yet to merge. In 1945, Einstein wrote a letter in response to a survey by a French mathematician who was trying to understand the thinking patterns of famous scientists. It can be found in Ideas and Opinions, a collection Einstein’s writings, and in it, he speaks about his process. “The words or the language, as they are written or spoken, do not seem to play any role in my mechanism of thought.The psychical entities which seem to serve as elements in thought are certain signs and more or less clear images which can be ‘voluntarily’ reproduced and combined. It is also clear that the desire to arrive finally at logically connected concepts is the emotional basis of this rather vague play with the above-mentioned elements. But taken from a psychological viewpoint, this combinatory playseems to be the essential feature in productive thought — before there is any connection with logical construction in words or other kinds of signs which can be communicated to others.” If you think about creativity as the ability to develop meaningful connections between existing parts of your reality, you can start to realize that creativity isn’t just reserved for the likes of Mozart and Picasso. It’s something that impacts all of our lives, and it’s something we all practice. Hone your mental inventory of knowledge and let it mingle in absurd ways. 4. Be Willing to Produce Subpar Work Like anything else in life, the only way to master creativity is to put in work. The difficulty, however, lies accepting the production of subpar work. Nobody likes to fall short of expectations, but it’s all the more daunting when it comes to creating because the result is a tangible output, like a painting or a book. One way to challenge this difficulty is to realize that we’re not the only ones that produce bad work. When we see a great creation by a genius, it’s useful to remember that they worked on more than just one piece. They produced a lot of really unsexy work that no one talks about. Over the course of his career, Einstein published over 300 scientific papers and about 150 non-scientific papers. An archive of his non-published work contained more than 30,000 unique documents, and he wasn’t always right. In Brilliant Blunder, Mario Livio predicts that about 20% of Einstein’s papers contain mistakes of sorts. A byproduct of his effort to think in unconventional ways was that his work was sometimes imperfect. 5. Compromise Today for Tomorrow Extraordinary results require extraordinary commitment. That’s the secret. John Hayes is a professor at Carnegie Mellon University and he once did a study to analyze thousands of musical pieces between 1685 and 1900. He was curious about how long it took for a musician to produce world class art. He narrowed it down to 500 masterpieces by 76 composers. By mapping out a timeline for each individual, he looked at when a piece was produced. Outside of only three artists, every composition was written at least a decade after they started to take their work seriously. In follow-up studies of poets and painters, he found the same result. He termed this “The ten years of silence” — a period with a high production of work but very little recognition. To cultivate creativity, you have to not only build the courage to produce bad work, but you also have put in a lot of unrewarded time to create great work. All You Need to Know If an artist is someone who produces something new and novel, then few people in history fit the bill like Einstein. Artistry was the source of his genius. This is what his story can teach us: I. Don’t wait for inspiration to get moving. Creativity is a process. Even the seemingly sporadic insights — like the ones we get in the shower — rely on what came before them. Inspiration doesn’t just strike for no reason. It relies on a consistent pattern of work that sometimes manifests itself in the form of those rare moments. To truly practice creativity, commit to a schedule, show up, and get to work, whether you want to or not. II. Seek relationships between existing ideas. Nothing new is completely original. Creativity is simply about producing something using a combination of the existing elements of your reality. Start by developing a mental inventory of relevant knowledge, work to connect the dots, and then support those connections with a logical structure. III. Produce a large volume of work. Creativity doesn’t work unless you do.Produce in the face of failure, and produce in the face of subpar results. It’s easy to forget that not every piece of work created by a genius was all that great. A lot of it wasn’t. It’s just not talked about. Creating bad work is necessary in order to uncover great work, and it all takes time. Mastering creativity is in itself an art, and like any art, it can empower you. The internet is noisy I write at Design Luck. It’s a free high-quality newsletter with unique insights that will help you live a good life. It’s well-researched and easy-going. Join 20,000+ readers for exclusive access. CreativityLifeLife LessonsSelf ImprovementEntrepreneurship One clap, two clap, three clap, forty? By clapping more or less, you can signal to us which stories really stand out. ￼ ￼￼￼￼￼ ￼Follow ￼ Zat Rana Medium member since May 2017 Playing at the intersection of science, art, and business. I write to reduce noise. www.designluck.com. CNBC, Business Insider, World Economic Forum, etc. ￼Follow ￼ Personal Growth Keep Learning. Keep Growing. More from Personal Growth Bad Habits You Must Break Immediately to Improve Your Life in the Next 100 Days ￼ Thomas Oppong ￼ ￼11K ￼ More on Self Improvement from Personal Growth 3 Ways To Attract The Mentor You Truly Want ￼ Nicolas Cole ￼ ￼1.4K ￼ Also tagged Entrepreneurship Your Company’s Culture is Who You Hire, Fire, & Promote ￼ Dr. Cameron Sepah ￼ ￼8.1K ￼ Responses ￼ Be the first to write a response… Alessandro Cerboni ￼ ￼ ￼ ￼ ￼￼￼￼

Disinformation is kind of a problem these days, yeah? Fatih Erikli uses a simulation that works like a disaster spread model applied to social networks to give an idea of how disinformation spreads. I tried to visualize how a disinformation becomes a post-truth by the people who subscribed in a network. We can think this network as a social media such as Facebook or Twitter. The nodes (points) in the map represent individuals and the edges (lines) shows the relationships between them in the community. The disinformation will be forwarded to their audience by the unconscious internet (community) members. Set the “consciousness” parameter and select a node to run.

Due to the interdisciplinary nature of complex systems as a field, students studying complex systems at University level have diverse disciplinary backgrounds. This brings challenges (e.g. wide range of computer programming skills) but also opportunities (e.g. facilitating interdisciplinary interactions and projects) for the classroom. However, there is little published regarding how these challenges and opportunities…

Official Post from Prof Steve Keen: This talk was a pleasure to give, because for once I was talking to an audience which completely understands Complex Systems (unlike the vast majority of economists). In the case of "EASY"--the "Evolutionary and Adaptive Systems Research Group"(http://www.sussex.ac.uk/easy/)--they apply this methodo

This talk was a pleasure to give, because for once I was talking to an audience which completely understands Complex Systems (unlike the vast majority of economists). In the case of "EASY"--the "Evolutionary and Adaptive Systems Research Group"(http://www.sussex.ac.uk/easy/)--they apply this methodology to analysing the brain and consciousness, rather than economics. In this talk I: Outline Minsky (downloadable from https://sourceforge.net/projects/minsky/), the system dynamics platform I designed for economics to enable banks, debt and money to be easily incorporated into dynamic models of the economy, explain why mainstream economists believe that you don't have to include banks, debt and money in macroeconomic models and why they are profoundly wrong, discuss the attempt by some Neoclassical economists to get back to that Olde Religion now that the global economy is reviving somewhat, ten years after the Global Financial Crisis, and conclude by showing that macroeconomics does not have to be derived from microeconomics (which is impossible in the first place, because of emergent properties in complex evolutionary systems, which the economy manifestly is), but can instead be derived directly from macroeconomic definitions in a Complex Systems manner.

Title: "Taming Complexity: From Network Science to Controlling Networks" Abstract: The ultimate proof of our understanding of biological or technologicaAbstract: The ultimate proof of our understanding of biological or technological systems is reflected in our ability to control them. While control theory offers mathematical tools to steer engineered and natural systems towards a desired state, we lack a framework to control complex self-organized systems. Here we explore the controllability of an arbitrary complex network, identifying the set of driver nodes whose time-dependent control can guide the system’s entire dynamics. We apply these tools to several real networks, unveiling how the network topology determines its controllability. Virtually all technological and biological networks must be able to control their internal processes. Given that, issues related to control deeply shape the topology and the vulnerability of real systems. Consequently unveiling the control principles of real networks, the goal of our research, forces us to address series of fundamental questions pertaining to our understanding of complex systems

author of the INCERTO a philosophical and practical essay on uncertainty (Antifragile , The Black Swan, Fooled by Randomness, and The Bed of Procrustes), a (so far) 4-volume "investigation of opacity, luck, uncertainty, probability, human error, risk,and decision making when we don’t understand the world, expressed in the form of a personal essay with autobiographical sections, stories, parables, and philosophical, historical, and scientific discussions in nonoverlapping volumes that can be accessed in any order." Amazon and B&N

How to be Rational about Rationality [One of the more technical (and optional) chapters, at the end of Skin of the Game] Rory Sutherland claims that the real function for swimming pools is allowing the middle class to sit around in bathing suits without looking ridiculous. Same with New York restaurants: you think their mission is to feed people, but that’s not what they do. They are in the business of selling you overpriced liquor or Great Tuscan wines by the glass, yet get you into the door by serving you your low-carb (or low-something) dishes at breakeven cost. (This business model, of course, fails to work in Saudi Arabia). So when we look at religion and, to some extent ancestral superstitions, we should consider what purpose they serve, rather than focusing on the notion of “belief”, epistemic belief in its strict scientific definition. In science, belief is literal belief; it is right or wrong, never metaphorical. In real life, belief is an instrument to do things, not the end product. This is similar to vision: the purpose of your eyes is to orient you in the best possible way, and get you out of trouble when needed, or help you find a prey at distance. Your eyes are not sensors aimed at getting the electromagnetic spectrum of reality. Their job description is not to produce the most accurate scientific representation of reality; rather the most useful one for survival.

The viable system model ( VSM) is a model of the organisational structure of any autonomous system capable of producing itself. A viable system is any system organised in such a way as to meet the demands of surviving in the changing environment. One of the prime features of systems that survive is that they are adaptable.

Empty The model was developed by operations research theorist and cybernetician Stafford Beer in his book Brain of the Firm (1972).[1] Together with Beer's earlier works on cybernetics applied to management, this book effectively founded management cybernetics. The first thing to note about the cybernetic theory of organizations encapsulated in the VSM is that viable systems are recursive; viable systems contain viable systems that can be modeled using an identical cybernetic description as the higher (and lower) level systems in the containment hierarchy (Beer expresses this property of viable systems as cybernetic isomorphism). A development of this model has originated the theoretical proposal called viable systems approach.

Dur­ing the Korean War, Korean and Chinese captors reportedly brainwashed American POWs held in prison camps. Several prisoners ultimately confessed to waging germ warfare -- which they hadn't -- and pledged allegiance to communism by th­e end of their captivity. At least 21 soldiers refused to come back to the United States when they were set free. ­It sounds impressive, but skeptics point ­out that it was 21 out of more than 20,000 prisoners in communist countries. Does brainwashing really work in any reliable way? In psychology, the study of brainwashing, often referred to as thought reform, falls into the sphere of "social influence." Social influence happens every minute of every day. It's the collection of ways in which people can change other people's attitudes, beliefs and behaviors. For instance, the compliance method aims to produce a change in a person's behavior and is not concerned with his attitudes or beliefs. It's the "Just do it" approach. Persuasion, on the other hand, aims for a change in attitude, or "Do it because it'll make you feel good/happy/healthy/successful." The education method (which is called the "propaganda method" when you don't believe in what's being taught) goes for the social-influence gold, trying to affect a change in the person's beliefs, along the lines of "Do it because you know it's the right thing to do." Brainwashing is a severe form of social influence that combine­s all of these approaches to cause changes in someone's way of thinking without that person's consent and often against his will.Brainwashing is the attempt to change the thoughts and beliefs of another person against their will. Learn about the science behind brainwashing.

Most businesses underestimate how hard it is to change people’s behavior. There is an assumption built into most marketing and advertising campaigns that if a business can just get your attention, give you a crucial piece of information about their brand, tell you about new features, or associate their brand with warm and fuzzy emotions, that they will be able to convince you to buy.

Here are the 50 most influential living psychologists, actively changing our understanding of ourselves and our often curious human behavior. True to the ancient namesake, these psychologists have taught us much about the human soul.

Did you know that the palm oil found in many of our lotions and cosmetics comes from the natural habitat of orangutans? Harvesting the oil damages their habitats and puts the animals at risk. Or that about a third of the calories grown in the world go to waste? Or that the equivalent of one dump truck of plastic enters the ocean ever minute? I didn’t, but the World Wildlife Foundation (WWF) and others are actively tackling these issues. These are all thorny, complex problems that require sustained behavior change to solve. Yet, historically, very little behavior change science — and even less behavior change design theory — has been applied to conservation efforts. That’s starting to change, thanks to work by the WWF, National Geographic, and others who recognize the need to apply the science of psychology to their efforts to save the planet. I had the honor of participating in the WWF’s annual Fuller Symposium on December 4–5 in Washington DC. The 2017 theme was “The Nature of Change: The Science of Influencing Behavior.” Speakers included experts in both social and environmental sciences, so the audience heard about theories of behavior change alongside case studies bringing those same theories to life.

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